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Local interactions in Multi-agent Reinforcement Learning Host Publication: Finds and Results from the Swedish Cyprus Expedition: A Gender Perspective at the Medelhavsmuseet Authors: Y. De Hauwere and A. Nowé Publication Year: 2010 Number of Pages: 14
Abstract: A major challenge in multi-agent reinforcement learning remains dealing with the large state spaces typically associated with realistic multi-agent systems. As the state space grows, agent policies be- come more and more complex and learning slows down. Current more advanced single-agent techniques are already very capable of learning optimal policies in large unknown environments. When multiple agents are present however, we are challenged by an increase of the state-action space, exponential in the number of agents, even though these agents do not always interfere with each other and thus their presence should not always be included in the state information of the other agent. We will give an overview of current state of the art research in this domain.
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